feat: MetonaAI Desktop 初始项目

- Electron + React + TypeScript 架构 - 三栏布局: Sidebar | ChatPanel | DetailPanel - 9 个内置工具 (文件系统/网络/记忆/命令) - SQLite 持久化 (better-sqlite3) - MUI 暗色/亮色主题系统 - Agent Loop ReAct 状态机引擎 - DeepSeek / Agnes AI / Ollama Provider 适配器 - MCP 协议集成 - 系统托盘 + 全局快捷键 - Tailwind CSS v4 + Tailwind Merge - 修复: Sidebar 缺失 TextField 导入导致黑屏
2026-06-27 21:33:27 +08:00
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+/**
+ * 记忆工具（2 个）
+ *
+ * memory_store, memory_search
+ *
+ * @see docs/MetonaAI-Desktop 架构与交互设计.html — 9 个基础工具
+ */
+
+import type { IMetonaTool, ToolExecutionContext } from '../../types/metona-tool';
+import type { MetonaToolDef } from '../../../harness/types';
+import { MetonaToolCategory, MetonaRiskLevel } from '../../../harness/types';
+import type { MemoryManager } from '../../memory/manager';
+
+// ===== 7. memory_store =====
+
+export class MemoryStoreTool implements IMetonaTool {
+  readonly definition: MetonaToolDef = {
+    name: 'memory_store',
+    description: 'Store a piece of information in persistent memory. Useful for remembering important facts, decisions, or user preferences across sessions.',
+    parameters: {
+      type: 'object',
+      properties: {
+        content: { type: 'string', description: 'The memory content to store' },
+        type: { type: 'string', description: 'Memory type: "episodic" (events), "semantic" (knowledge), or "working" (task state)', enum: ['episodic', 'semantic', 'working'] },
+        importance: { type: 'number', description: 'Importance score 0-1 (default 0.5)' },
+        source: { type: 'string', description: 'Source identifier (default "agent")' },
+        tags: { type: 'array', description: 'Tag list for categorization', items: { type: 'string', description: 'Tag' } },
+      },
+      required: ['content', 'type'],
+    },
+    category: MetonaToolCategory.DATABASE,
+    riskLevel: MetonaRiskLevel.MEDIUM,
+    requiresPermission: false,
+    timeoutMs: 10_000,
+  };
+
+  constructor(private memoryManager: MemoryManager) {}
+
+  async execute(args: Record<string, unknown>, context: ToolExecutionContext): Promise<unknown> {
+    const content = args.content as string;
+    const type = args.type as 'episodic' | 'semantic' | 'working';
+    const importance = (args.importance as number) ?? 0.5;
+    const source = (args.source as string) ?? 'agent';
+    const tags = (args.tags as string[]) ?? [];
+
+    const id = await this.memoryManager.store({
+      type,
+      content,
+      source: source as 'user_input' | 'tool_result' | 'agent_thought' | 'imported',
+      importance,
+      sessionId: context.sessionId,
+    });
+
+    return { id, type, content_preview: content.slice(0, 100), importance };
+  }
+}
+
+// ===== 8. memory_search =====
+
+export class MemorySearchTool implements IMetonaTool {
+  readonly definition: MetonaToolDef = {
+    name: 'memory_search',
+    description: 'Search persistent memory for relevant information. Returns memories sorted by relevance.',
+    parameters: {
+      type: 'object',
+      properties: {
+        query: { type: 'string', description: 'Search query or keywords' },
+        type: { type: 'string', description: 'Filter by memory type', enum: ['episodic', 'semantic', 'working'] },
+        topK: { type: 'number', description: 'Number of results (default 5)' },
+        threshold: { type: 'number', description: 'Minimum relevance score 0-1 (default 0.7)' },
+      },
+      required: ['query'],
+    },
+    category: MetonaToolCategory.DATABASE,
+    riskLevel: MetonaRiskLevel.SAFE,
+    requiresPermission: false,
+    timeoutMs: 10_000,
+  };
+
+  constructor(private memoryManager: MemoryManager) {}
+
+  async execute(args: Record<string, unknown>, _context: ToolExecutionContext): Promise<unknown> {
+    const query = args.query as string;
+    const type = args.type as 'episodic' | 'semantic' | 'working' | undefined;
+    const topK = (args.topK as number) ?? 5;
+    const threshold = (args.threshold as number) ?? 0.7;
+
+    const results = await this.memoryManager.search(query, {
+      topK,
+      type,
+      minImportance: threshold,
+    });
+
+    return {
+      query,
+      results: results.map((r) => ({
+        id: r.id,
+        type: r.type,
+        content: r.content.slice(0, 500),
+        importance: r.importance,
+        score: r.score,
+      })),
+      count: results.length,
+    };
+  }
+}